Septicemia, a Clinical syndrome requiring urgent medical attention, is associated with significant morbidity and mortality in end stage renal disease (ESRD). Between 1988 and 1990, septicemia was the fourth leading cause of death among patients with ESRD, accounting for 21.5 deaths per 1000 patient-years at risk, or 11% of deaths with an identifiable cause. In 1990, septicemia accounted for over 5,000 hospital admissions and 55,000 hospital days among ESRD patients treated under the Medicare program. Preliminary data from the United States Renal Data System (USRDS) suggest that death rates due to septicemia vary markedly according to type of dialysis management, underlying cause of renal failure, sociodemographic characteristics and, comorbidity of ESRD. Other biomedical data suggest at among hemodialysis patients the risk of septicemia varies according to the type of vascular access used and nutritional status (e.g., the level of serum albumin). However, risk factors for septicemia and death due to septicemia have not been fully elucidated due in part to lack of comprehensive data on a large group of patients. We propose a study to investigate whether particular ESRD patient characteristics (clinical, treatment and sociodemographic) are associated with septicemia incidence and prognosis. We will use data from the USRDS and several other complementary sources. We will examine five related issues. First, we will compare the incidence of septicemia a) for hemodialysis patients versus peritoneal dialysis patients, and b) for hemodialysis patients with different vascular access (permanent subclavian catheter versus temporary line versus arteriovenous graft versus fistula). Second, we will compare the incidence of septicemia death a) for hemodialysis versus peritoneal dialysis patients, and b) for hemodialysis patients with different vascular access. Third, we will compare the prognosis for survival following hospitalization for septicemia in hemodialysis versus peritoneal dialysis patients. Fourth, we will compare the prognosis of hospitalization for dialysis patients with versus without a history of septicemia hospitalization. Finally, we will compare the inpatient costs and hospital days for septicemia between hemodialysis and peritoneal dialysis patients. These issues will be explored with multivariate statistical methods, including multiple logistic regression, proportional hazards or multiple linear regression models, to adjust for confounding characteristics that may confound the relationship between the outcome and primary predictor variables. This study will provide information that can be used by physicians to identify ESRD patients at highest risk for septicemia, and to plan and implement interventions designed to reduce septicemia incidence, and its associated morbidity and mortality for ESRD patients.